What are qualitative, quantitative, and mixed methods in research methodologies?
What are the options around sampling, data collection methods, and data analysis?
How do you choose the right research methodology for your project?
Understanding Research Methodology
Definition: The 'how' of your research, detailing what you do to address your research question. This includes deciding who to collect data from, how to collect it, and how to analyze it.
Context: Comes after the introduction and literature review chapters in a thesis.
Importance: Essential for demonstrating that you understand your research background and how previous studies have addressed your research problem.
Key Components of Methodology
Data Collection: What data you collected, who or where you got it from.
Methods: How you collected data (e.g., surveys, interviews).
Analysis: How you analyzed the data.
Clarity: Must be clear enough that someone else could replicate your study.
Qualitative, Quantitative, and Mixed Methods
Definitions
Quantitative: Data in the form of numbers; measurable and countable.
Qualitative: Data in the form of ideas, words, and phrases; not numerically measured.
Mixed Methods: Combination of both quantitative and qualitative data.
Philosophies
Positivist: Theory or hypothesis-driven, uses data to test theories or hypotheses, often linked to quantitative data.
Interpretivist: Data-driven, uses data to generate theories or hypotheses, often linked to qualitative data.
Sampling Methods
Types
Probability Sampling: Likely to be representative of the population, ideal for generalizability.
Non-Probability Sampling: Based on convenience or other factors, not generalizable to the entire population but valid within their context.
Data Collection Methods
Common Methods
Qualitative: Interviews, focus groups, document analyses, ethnographic or observational methods.
Quantitative: Surveys, measurements using instruments (e.g., CT scanners, rulers).
Data Analysis
Qualitative Data Analysis
Content Analysis: Identifying themes from data.
Discourse Analysis: Understanding power dynamics and communication styles in interactions.
Narrative Analysis: Examining how stories are told and their underlying meanings.
Quantitative Data Analysis
Descriptive Statistics: Averages, means, understanding the basic nature of data.
Inferential Statistics: Correlations, regressions, comparing datasets, and understanding relationships between variables.
Choosing the Right Methodology
Key Factors
Nature of the Research: Exploratory vs. confirmatory research.
Practical Considerations: Access to participants, resources, and tools.
Research Questions: The methodology must be designed to answer the research questions effectively.
Recap
Start with the research question and objectives.
Move on to deciding if your approach will be exploratory (qualitative) or confirmatory (quantitative).
Consider practical aspects like budget, tools, and participant availability.